1. Field of the Invention
The present invention relates to a noise eliminating circuit suitably used for preprocessing immediately before encoding an input signal.
2. Description of the Prior Art
It is known that an apparatus for compressing and decompressing an input image signal often has noise eliminating means immediately in front of an encoder provided in a data compression system of the apparatus. Of noise eliminating circuits used for the noise eliminating means, a noise eliminating circuit based on three-dimensional processing is known.
FIG. 10 shows a block diagram of an example of the above-mentioned noise eliminating circuit. In the figure, a terminal 11 is supplied with a digitally converted input signal (image signal) for example. The input signal is supplied to a noise eliminating filter for stationary image part 12 if an input image based on pixels constituting the input signal is the stationary image part and a noise eliminating filter for moving image part 13 if the input image is the moving image part. The filters 12 and 13 perform noise elimination processing on the input signal according to contents of the input image. Output from each of the filters is sent to a switch 20.
The input image is also supplied to a motion detector 30 which detects a motion of the input image on a pixel basis. The switch 20 is adaptively operated by motion control output according to the detected motion of the input image. Thus, a pixel in the stationary image part is noise-eliminated by a time filter which performs filter processing relative to time and a dynamic, moving pixel is noise-eliminated through a spatial filter.
Thus, performing noise elimination by adaptively selecting between the filters according to a movement of an input image achieves noise elimination without degrading a picture quality of the input image.
The noise eliminating filter for stationary image 12 is a simple mean-value filter having a frame memory 15. In this filter, a memory output value from a preceding frame is multiplied by k (0&lt;k&lt;1) in a coefficient multiplier 16 and a resulting value is added in an adder 18 to a value obtained by multiplying an input image of a current frame supplied to the input terminal 11 by (1-k) in a coefficient multiplier 17. A resultant value provides a filter output.
FIG. 11 describes an operation of the noise eliminating filter 12. If a random noise indicated by a dot is introduced in a particular pixel of each frame and k=0.5, then noise levels a, b, c and d get smaller sequentially by the second power due to a filter effect in time of the noise eliminating filter 12.
The noise eliminating filter for moving image part 13 is an intermediate-value filter such as a median filter, a type of a spatial filter. The intermediate-value filter uses a level of a pixel which is intermediate between levels of two pixels before and after a pixel in attention as a level of the pixel in attention. FIG. 12 describes an operation of this filter.
For an input image variation like a curve P, if noise n is introduced in pixel b in attention (an intrinsic level of the pixel is also b) for example, an intermediate value among a, n and c is selected; that is, c is selected. Since, in a next pixel, n is smaller than d, the noise n is selected for the first time. Since this noise level is lower than d, even if the noise n is selected, it does not extremely stand out from pixels around it and therefore is not prominent so much.
In this connection, a normal output without filtering results in a pixel level of FIG. 12 and the noise n is selected when the pixel level is low, making the noise level stand out and the selected noise n prominent.
FIG. 13 describes detection of a motion of an input image. In the figure, a difference between each of 3.times.3 pixels around pixel e in attention in a current frame (nth frame) and each of the same pixel locations in a preceding frame (n-1 frame) is obtained (a-a', b-b', . . . i-i'). Then sum S of the differences is obtained.
A value of the sum S is compared with a predetermined threshold value. If the sum S is greater than the threshold value, a pixel in attention at the time is determined to be a moving pixel (moving image part); if the sum S is smaller than the threshold value, the pixel in attention is determined to be a stationary pixel (stationary image part).
However, since a conventional noise eliminating circuit having the above-mentioned constitution uses a time filter (mean-value filter), an averaged output remains to an end.
For example, if a noise (of noise level a) gets in a pixel 1 of the nth frame as shown in FIG. 11, the noise component will not disappear several frames later. Effects of the noise will remain for long, accompanying an after-image accordingly.
Besides, since an influence to be given by a noise to an immediately succeeding frame is as large as 1/2, a picture quality in transition from a moving image part to a stationary image part is not improved effectively.